Integrated data analysis

ABSTRACT

Systems and methods are provided for integrated data analysis. At least one object that is responsive to a first search query is determined. The object is stored in an object model that is managed by a first computing platform, and the at least one object is associated with one or more properties. One or more data sets that are responsive to a second search query are determined. The data sets are managed by a second computing platform. The one or more data sets are determined related to the at least one object. The at least one object is updated to include at least one property that references at least one analysis that relies on the one or more data sets.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. Ser. No. 16/368,527, filedMar. 28, 2019, which is a continuation of U.S. Ser. No. 15/474,719,filed Mar. 30, 2017, now U.S. Pat. No. 10,289,711, which claims thebenefit under 35 U.S.C. § 119(e) of U.S. Provisional Applications Ser.No. 62/442,210 filed Jan. 4, 2017, the content of which is incorporatedby reference in its entirety into the present disclosure.

FIELD OF THE INVENTION

This disclosure relates to cross-platform data integration.

BACKGROUND

Under conventional approaches, isolated data platforms typically do notcross link to one another. Users operating one of the platforms areunable to simultaneously utilize resources in other platforms or tocreate legacy work for collaborators accessing through the otherplatforms. Such system prevents synergy, limits efficiency, and causesincomplete work product.

SUMMARY

Various embodiments of the present disclosure can include systems,methods, and non-transitory computer readable media configured toperform integrated data analysis. At least one object that is responsiveto a first search query is determined. The object is stored in an objectmodel that is managed by a first computing platform, and the at leastone object is associated with one or more properties. One or more datasets that are responsive to a second search query are determined. Thedata sets are managed by a second computing platform. The one or moredata sets are determined related to the at least one object. The atleast one object is updated to include at least one property thatreferences at least one analysis that relies on the one or more datasets.

In some embodiments, the analysis is accessible to other users of thecomputing system when interacting with the at least one object.

In some embodiments, the first computing platform is configured to storedata in one or more object models.

In some embodiments, the second computing platform is configured tostore the data sets in one or more tables.

In some embodiments, the object is defined by object componentsincluding at least one of: property, media, note, or relationship withanother object.

In some embodiments, the object is associated with a person.

In some embodiments, the one or more data sets are configured to storerecords of people.

In some embodiments, to update the at least one object to include the atleast one property that references the at least one analysis that relieson the one or more data sets, the systems, methods, and non-transitorycomputer readable media are configured to provide an option to link theanalysis to the at least one object, receive a user operation inresponse to the provided option, and update the at least one object toinclude the at least one property based on the received operation.

In some embodiments, the analysis is generated based on filtering.

In some embodiments, the systems, methods, and non-transitory computerreadable media are further configured to provide one or more of theanalyses through an interface.

These and other features of the systems, methods, and non-transitorycomputer readable media disclosed herein, as well as the methods ofoperation and functions of the related elements of structure and thecombination of parts and economies of manufacture, will become moreapparent upon consideration of the following description and theappended claims with reference to the accompanying drawings, all ofwhich form a part of this specification, wherein like reference numeralsdesignate corresponding parts in the various figures. It is to beexpressly understood, however, that the drawings are for purposes ofillustration and description only and are not intended as a definitionof the limits of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

Certain features of various embodiments of the present technology areset forth with particularity in the appended claims. A betterunderstanding of the features and advantages of the technology will beobtained by reference to the following detailed description that setsforth illustrative embodiments, in which the principles of the inventionare utilized, and the accompanying drawings of which:

FIG. 1 illustrates an example environment for performing integrated dataanalysis, in accordance with various embodiments.

FIG. 2 illustrates an example system for performing integrated dataanalysis, in accordance with various embodiments.

FIG. 3 illustrates an example system for performing integrated dataanalysis, in accordance with various embodiments.

FIGS. 4A-D illustrate example interfaces for performing integrated dataanalysis, in accordance with various embodiments.

FIG. 5 illustrates a flowchart of an example method, in accordance withvarious embodiments.

FIG. 6 illustrates a flowchart of an example method, in accordance withvarious embodiments.

FIG. 7 illustrates a block diagram of an example computer system inwhich any of the embodiments described herein may be implemented.

DETAILED DESCRIPTION

In some instances, multi-platform collaboration may be needed to providea more complete view of a project (e.g., an analysis). For example, afirst platform may manage data using an object model while a secondplatform may store structured data (e.g., database tables) andunstructured data (e.g., text files). In the absence of any link betweenthese two platforms, any analysis done in the first platform typicallycannot be associated to relevant data stored in the second platform andvice versa. This deficiency can result in an incomplete view ofanalysis.

Further, under conventional approaches, it is difficult to establishlinks among existing projects built according to some individualplatform's format. In one example, a personal profile object may becreated in a first platform and a set of tabular data relevant to theprofile may be created in a second platform. A user using either of theplatforms to build an analysis is likely to overlook the existinginformation in the other platform if the platforms operateindependently. Moreover, work collaboration may be limited because ofthe unlinked data platforms. Since each platform is independent, anyanalysis performed in one platform is typically not associated with ananalysis performed in another platform. This deficiency may cause thesame work to be unnecessarily duplicated.

A claimed solution rooted in computer technology overcomes problemsspecifically arising in the realm of computer technology. In variousimplementations, a computing system may integrate two differentplatforms to facilitate data analysis. For example, a first platform maybe configured to store and manage data using at least one object modelwhile a second platform may be configured to store structured and/orunstructured data (e.g., one or more data sets in tables or otherformats). An object model can store data as objects defined by objectcomponents including properties, media (e.g., files, images, etc.),notes, and/or relationships with other objects. In variousimplementations, the system may allow a user (e.g., an analyst) to runsearches in the first platform to identify various objects that areresponsive to the user's query. The system may also allow the user torun searches in the second platform to identify data that is responsiveto the user's query. The user may modify or other manipulate theidentified data (e.g., filtering the data to obtain an analysis). Insome implementations, the user can identify relationships betweenobjects (e.g., an object referencing a person) from the first platformand structured data (e.g., a database table including transactionsrecords that match an attribute of the person such as driver's licensenumber, a database table obtained in the analysis, etc.) from the secondplatform. In this example, the user can select one or more options tolink the relevant structured data to the person object. As such, datastored in the two different platforms can be linked and an analysisbuilt upon any part of the data can be made available to users accessingeither platform. Similarly, the benefit applies to more than twoplatforms. Further, the system may provide all linked data of the sameobject. Thus, a user can view, review, or build upon existing worksrelated to the same object.

FIG. 1 illustrates an example environment 100 for performing integrateddata analysis, in accordance with various embodiments. As shown in FIG.1, the example environment 100 can include at least one computing system102 that includes one or more processors 104 and memory 106. The memory106 may be non-transitory and computer-readable. The memory 106 maystore instructions that, when executed by the one or more processors104, cause the one or more processors 104 to perform various operationsdescribed herein. The environment 100 may include a computing device 112coupled to the system 102. The environment 100 may also include a firstcomputing platform 108 and a second computing platform 110 bothaccessible to the system 102. For example, the first computing platform108 may include one or more searchable object models. That is, the firstplatform 108 may be configured to store and manage data using at leastone object model. An object model can store data as objects defined byobject components, which can include properties (e.g., textual objectattributes such as names, emails, etc.), media (e.g., files, images,videos, binary data, etc.), notes (e.g., free text containers), and/orrelationships with other objects. The second computing platform 110 mayinclude one or more searchable databases. That is, the second platform110 may be configured to store structured and/or unstructured data(e.g., one or more data sets in tables or other formats).

In some embodiments, the system 102 and the computing device 112 may beintegrated in a single device or system. Alternatively, the system 102and the computing device 112 may operate individually, for example, thecomputing device 112 may be a mobile device and the system 102 may be aserver. The first computing platform 108 and the second computingplatform 110 may be stored anywhere accessible to the system 102, forexample, in the memory 106, in another device coupled to the system 102,etc. Various operations of the system 102 are described below inreference to FIG. 2 to FIG. 6.

FIG. 2 illustrates an example system for performing integrated dataanalysis, in accordance with various embodiments. The operations shownin FIG. 2 and presented below are intended to be illustrative.

In various embodiments, the computing device 112 may receive a firstsearch query 202 (e.g., a search query for a person) and transmit thefirst search query 202 to the system 102. In various embodiments,queries and/or data may be transmitted between computing devices (orsystems) over one or more computer networks (e.g., local area networks,the Internet, etc.). The system 102 may use the first computing platform108 to determine at least one object 204 that is responsive to the firstsearch query 202. The object may be stored in an object model that ismanaged by the first computing platform 108 and the at least one objectmay be associated with one or more properties. In some embodiments, thesystem 102 can submit the first search query 202 to the first computingplatform 108 and the first computing platform 108 can provide the system102 with the at least one object 204 that is responsive to the firstsearch query 202. In some embodiments, when executing the first searchquery 202, the system 102 can be configured to search the firstcomputing platform 108 for objects that are responsive to the firstsearch query 202 and these objects can be organized into the at leastone determined object 204.

In various embodiments, the computing device 112 may also receive asecond search query 206 (e.g., a search query for a database tablerecord) and transmit the second search query 206 to the system 102. Thesystem 102 may use the second computing platform 110 to determine one ormore data sets 208 that are responsive to the second search query 206.The data sets 208 are managed by the second computing platform 110. Insome embodiments, the system 102 can submit the second search query 206to the second computing platform 110 and the second computing platform110 can provide the system 102 with the one or more data sets 208 thatare responsive to the second search query 206. In some embodiments, whenexecuting the second search query 206, the system 102 can be configuredto search the second computing platform 110 for data sets that areresponsive to the second search query 206, and these objects can beorganized into the one or more data sets 208.

In various embodiments, the first computing platform 108 is configuredto store data in one or more object models and the second computingplatform 110 is configured to store the data sets in one or more tables.As described above, an object model can store data as objects and eachobject can be defined by object components including properties, media,notes, and relationships with other objects. Tabular data sets may be,for example, in a CSV (Comma Separated Values) format.

In various embodiments, the system 102 may determine that the one ormore data sets 208 are related to the at least one object 204. Thedetermined one or more data sets 208 may be provided to a user foranalysis. The system 102 can then update the at least one object 204through an object update 210 to include at least one property thatreferences at least one analysis that relies on the one or more datasets 208. For example, a user may input an instruction to associate oneor more fields of the data sets (e.g., a column of an analysis table)with a property (e.g., name) of the at least one object 204. That is, auser may identify relationships between objects (e.g., an objectreferencing a person) from the first computing platform 108 andstructured data (e.g., a database table including records that match anattribute of the person such as driver's license number) from the secondcomputing platform 110. In some embodiments, the user can select one ormore options to link the relevant structured data to the person object.More details of this step are described below in reference to FIGS. 3and 4C.

In various embodiments, the system 102 may provide data sets andanalyses linked with the object. Thus, all analyses are accessible toother users of the computing system 102 when interacting with the atleast one object 204. The accessibility enables future work related tothe object to build upon existing analysis and prevents repetitiveefforts. Further, a user can extract information from previous analysesby tracing from the stored analysis to the associated objects. Moredetails of this step are described below in reference to FIG. 4D.

FIG. 3 illustrates an example system for performing integrated dataanalysis, in accordance with various embodiments. The operations shownin FIG. 3 and presented below are intended to be illustrative.

In various embodiments, updating the at least one object 204 through theobject update 210 to include the at least one property that referencesthe at least one analysis which relies on the one or more data sets 208may comprise the following steps. The system 102 may provide at thecomputing device 112 an option to link the analysis to the at least oneobject 204. The analysis relying on the one or more data sets 208 maybe, for example, created by selecting, filtering, or consolidating theone or more data sets 208. Alternatively, the analysis may be createdvia other techniques based on the one or more data sets 208. The system102 may receive through the computing device 112 a user operation inresponse to the link option. The operation may select at least a part ofthe analysis (e.g., a column and/or a field) to link with at least apart of the object (e.g., a property such as name). The system 102 mayupdate the at least one object 204 to include the at least one propertybased on the received operation.

FIG. 4A-4D illustrate example interfaces for performing integrated dataanalysis, in accordance with various embodiments. The description ofFIGS. 4A-4D are intended to be illustrative and may be modified invarious ways according to the implementation. Various interfacesillustrated in FIGS. 4A-4D and described below may be provided at thecomputing device 112 and/or the system 102 described above. In someembodiments, the interfaces may be presented through a respectivedisplay screen of the computing device 112 and/or the system 102. Insome embodiments, the interfaces may be provided by a softwareapplication running on the computing device 112 and/or the system 102.

In some embodiments, as shown in FIG. 4A, a user may be given someinformation as appearing in interface 400. The user identifies a name“John Doe” and attempts to conduct some analysis. The user may highlightand search for this name as the first search query 202. In response, thesystem 102 may search the first computing platform 108 and return the atleast one determined object 204 in an interface 402. The user may openthis identified object “John Doe” as discussed below in reference toFIG. 4B.

In some embodiments, as shown in FIG. 4B, interface 410 opens up to showthe object “John Doe.” The object may be defined by object componentssuch as properties, media, notes, or relationships with other objects.Tabs 412 comprise a number of commands, such as “properties,” “media,”“links,” “raw data sets,” and “derived analyses.” The properties objectcomponent may be linked to the “properties” tab, the media objectcomponent may be linked to the “media” tab, and the relationships objectcomponent may be linked to the “links” tab. Selecting the “raw datasets” tab may submit the second search query 206 for raw data sets. Theresults responsive to the second search query can be presented throughthe interface 414. The results responsive to the second search query areretrieved from the second computing platform and may each compriseunderlying data (e.g., metadata) of the object. Selecting the “derivedanalyses” tab may look for, display, and/or load derived analysisproperties associated with the object “John Doe.” The “derived analyses”tab is described in more detail below in reference to FIG. 4D.

In the example of FIG. 4B, the “raw data sets” tab has been selected. Inresponse, one or more raw data sets are presented in interface 414. Thisoperation allows access to the data sets stored in the second computingplatform from the first computing platform. As shown, both the data setinformation (e.g., raw data sets 1-4 presented in the interface 414 andthe object information (e.g., properties, media, and links linkedthrough the tabs 412) are accessible through one interface. Further, thesystem 102 may determine one or more data sets that are related to theat least one object. For example, as shown, raw data set 3 (i.e., thedata set presented in interface 416) is determined to match to the “JohnDoe” object. The data set presented in the interface 416 comprises a“date” column, an “account holder” column, an “ID” column, etc. Todetermine the matched raw data set, the system 102 may automaticallycompare the target object with the stored data sets based on one or morecriteria (e.g., property matches). That is, this comparison may beperformed without any user input. For example, the system 102 may searchand compare an “ID” property (e.g., social security number, traderidentification number, email address) of the object with an “ID” columnin the data sets. In another example, the system 102 may compareactivity patterns for the object and the datasets. The matched raw dataset presented in the interface 416 may correspond to the one or moredetermined data sets 208. Since the raw data sets presented in theinterface 414 may be too comprehensive, retrieving the most relevantdata as the matched raw data set can help increase work efficiency andfacilitate analysis.

In some embodiments, the matched raw data set may be presented as atable in the interface 416. By opening the table, the user can furthermanipulate the data in the matched raw data set. For example, the usercan filter the matched raw data set data by “account holder,” “date,”and/or other criteria as part of an analysis.

In some embodiments, as shown in FIG. 4C, an interface 420 for object“John Doe” is presented. Specifically, an analysis 424 is obtained byextracting matched raw data sets that are associated with a specifiedname (e.g., “John Doe”) as the account holder, along with otherassociated information such as “date,” “ID,” “record,” and “price”populated in various columns of a table 426. Further, an interface 422is provided for updating the object “John Doe” to include at least oneobject property (e.g., the name property as determined in selectionoption 425) that references the analysis 424 (e.g., referencing the“account holder” column 427 of the table 426 through the selectionoption 423), the analysis 424 relying on the one or more data setspresented in the interface 416 described above. This update may becompleted in various methods. As shown, a column of the table 426 (e.g.,the “account holder” column 427) and a property of the current object(e.g., object name) can be selected and linked. Alternatively, variousfields other than table columns may be used to reference the analysis.By searching, the selected object property at selection option 425 willbring up the associated object in interface 428. Then, by executing thelink command, the selected name property of the object will be updatedto reference the analysis 424. In this example, the analysis 424 relieson the data sets stored in the second computing platform. As such,object data information from the first computing platform and data setinformation from the second computing platform are linked, so that userscan intuitively explore the data set information from the object modelor vice versa.

In some embodiments, as shown in FIG. 4D, an interface 430 presents theobject (e.g., “John Doe” object) and its associated “derived analyses”after the update. Since the “account holder” column 427 of the table 426described above has been associated with the object name of the “JohnDoe” object, the analysis (John Doe) 436 appears under the “derivedanalyses” tab along with any other existing analysis, such as theprevious analysis (other suspects) 432. As such, related analysescreated by different users at different times can be rendered togetherfor further comparison and study. For example, the previous analysis(other suspects) 432 may be opened up in interface 434 to showinformation such as “similarity” to John Doe, “account holder,” “ID,”“record,” and “price.” Similar to the linking process above, the“account holder” column 435 can be searched in interface 436 forassociated object names. In turn, interface 438 opens up and shows theobjects associated with the previous analysis 432 for furtherinvestigation.

FIG. 5 illustrates a flowchart of an example method 500, according tovarious embodiments of the present disclosure. The method 500 may beimplemented in various environments including, for example, theenvironment 100 of FIG. 1. The operations of method 500 presented beloware intended to be illustrative. Depending on the implementation, theexample method 500 may include additional, fewer, or alternative stepsperformed in various orders or in parallel. The example method 500 maybe implemented in various computing systems or devices including one ormore processors.

At block 502, at least one object that is responsive to a first searchquery is determined. The object is stored in an object model that ismanaged by a first computing platform, and the at least one object isassociated with one or more properties. At block 504, one or more datasets that are responsive to a second search query are determined. Thedata sets are managed by a second computing platform. At block 506, theone or more data sets are determined related to the at least one object.At block 508, the at least one object is updated to include at least oneproperty that references at least one analysis that relies on the one ormore data sets.

FIG. 6 illustrates a flowchart of an example method 600, according tovarious embodiments of the present disclosure. The method 600 may beimplemented in various environments including, for example, theenvironment 100 of FIG. 1. The operations of method 600 presented beloware intended to be illustrative. Depending on the implementation, theexample method 600 may include additional, fewer, or alternative stepsperformed in various orders or in parallel. The example method 600 maybe implemented in various computing systems or devices including one ormore processors.

At block 602, an option is provided to link an analysis to at least oneobject. At block 604, a user operation in response to the providedoption is received. At block 606, the at least one object is updatedbased on the received operation to include at least one property thatreferences the at least one analysis. The at least one analysis relieson one or more data sets.

Hardware Implementation

The techniques described herein are implemented by one or morespecial-purpose computing devices. The special-purpose computing devicesmay be hard-wired to perform the techniques, or may include circuitry ordigital electronic devices such as one or more application-specificintegrated circuits (ASICs) or field programmable gate arrays (FPGAs)that are persistently programmed to perform the techniques, or mayinclude one or more hardware processors programmed to perform thetechniques pursuant to program instructions in firmware, memory, otherstorage, or a combination. Such special-purpose computing devices mayalso combine custom hard-wired logic, ASICs, or FPGAs with customprogramming to accomplish the techniques. The special-purpose computingdevices may be desktop computer systems, server computer systems,portable computer systems, handheld devices, networking devices or anyother device or combination of devices that incorporate hard-wiredand/or program logic to implement the techniques.

Computing device(s) are generally controlled and coordinated byoperating system software, such as iOS, Android, Chrome OS, Windows XP,Windows Vista, Windows 7, Windows 8, Windows Server, Windows CE, Unix,Linux, SunOS, Solaris, iOS, Blackberry OS, VxWorks, or other compatibleoperating systems. In other embodiments, the computing device may becontrolled by a proprietary operating system. Conventional operatingsystems control and schedule computer processes for execution, performmemory management, provide file system, networking, I/O services, andprovide a user interface functionality, such as a graphical userinterface (“GUI”), among other things.

FIG. 7 is a block diagram that illustrates a computer system 700 uponwhich any of the embodiments described herein may be implemented. Thecomputer system 700 includes a bus 702 or other communication mechanismfor communicating information, one or more hardware processors 704coupled with bus 702 for processing information. Hardware processor(s)704 may be, for example, one or more general purpose microprocessors.

The computer system 700 also includes a main memory 706, such as arandom access memory (RAM), cache and/or other dynamic storage devices,coupled to bus 702 for storing information and instructions to beexecuted by processor 704. Main memory 706 also may be used for storingtemporary variables or other intermediate information during executionof instructions to be executed by processor 704. Such instructions, whenstored in storage media accessible to processor 704, render computersystem 700 into a special-purpose machine that is customized to performthe operations specified in the instructions.

The computer system 700 further includes a read only memory (ROM) 708 orother static storage device coupled to bus 702 for storing staticinformation and instructions for processor 704. A storage device 710,such as a magnetic disk, optical disk, or USB thumb drive (Flash drive),etc., is provided and coupled to bus 702 for storing information andinstructions.

The computer system 700 may be coupled via bus 702 to a display 712,such as a cathode ray tube (CRT) or LCD display (or touch screen), fordisplaying information to a computer user. An input device 714,including alphanumeric and other keys, is coupled to bus 702 forcommunicating information and command selections to processor 704.Another type of user input device is cursor control 716, such as amouse, a trackball, or cursor direction keys for communicating directioninformation and command selections to processor 704 and for controllingcursor movement on display 712. This input device typically has twodegrees of freedom in two axes, a first axis (e.g., x) and a second axis(e.g., y), that allows the device to specify positions in a plane. Insome embodiments, the same direction information and command selectionsas cursor control may be implemented via receiving touches on a touchscreen without a cursor.

The computing system 700 may include a user interface module toimplement a GUI that may be stored in a mass storage device asexecutable software codes that are executed by the computing device(s).This and other modules may include, by way of example, components, suchas software components, object-oriented software components, classcomponents and task components, processes, functions, attributes,procedures, subroutines, segments of program code, drivers, firmware,microcode, circuitry, data, databases, data structures, tables, arrays,and variables.

In general, the word “module,” as used herein, refers to logic embodiedin hardware or firmware, or to a collection of software instructions,possibly having entry and exit points, written in a programminglanguage, such as, for example, Java, C or C++. A software module may becompiled and linked into an executable program, installed in a dynamiclink library, or may be written in an interpreted programming languagesuch as, for example, BASIC, Perl, or Python. It will be appreciatedthat software modules may be callable from other modules or fromthemselves, and/or may be invoked in response to detected events orinterrupts. Software modules configured for execution on computingdevices may be provided on a computer readable medium, such as a compactdisc, digital video disc, flash drive, magnetic disc, or any othertangible medium, or as a digital download (and may be originally storedin a compressed or installable format that requires installation,decompression or decryption prior to execution). Such software code maybe stored, partially or fully, on a memory device of the executingcomputing device, for execution by the computing device. Softwareinstructions may be embedded in firmware, such as an EPROM. It will befurther appreciated that hardware modules may be comprised of connectedlogic units, such as gates and flip-flops, and/or may be comprised ofprogrammable units, such as programmable gate arrays or processors. Themodules or computing device functionality described herein arepreferably implemented as software modules, but may be represented inhardware or firmware. Generally, the modules described herein refer tological modules that may be combined with other modules or divided intosub-modules despite their physical organization or storage.

The computer system 700 may implement the techniques described hereinusing customized hard-wired logic, one or more ASICs or FPGAs, firmwareand/or program logic which in combination with the computer systemcauses or programs computer system 700 to be a special-purpose machine.According to one embodiment, the techniques herein are performed bycomputer system 700 in response to processor(s) 704 executing one ormore sequences of one or more instructions contained in main memory 706.Such instructions may be read into main memory 706 from another storagemedium, such as storage device 710. Execution of the sequences ofinstructions contained in main memory 706 causes processor(s) 704 toperform the process steps described herein. In alternative embodiments,hard-wired circuitry may be used in place of or in combination withsoftware instructions.

The term “non-transitory media,” and similar terms, as used hereinrefers to any media that store data and/or instructions that cause amachine to operate in a specific fashion. Such non-transitory media maycomprise non-volatile media and/or volatile media. Non-volatile mediaincludes, for example, optical or magnetic disks, such as storage device710. Volatile media includes dynamic memory, such as main memory 706.Common forms of non-transitory media include, for example, a floppydisk, a flexible disk, hard disk, solid state drive, magnetic tape, orany other magnetic data storage medium, a CD-ROM, any other optical datastorage medium, any physical medium with patterns of holes, a RAM, aPROM, and EPROM, a FLASH-EPROM, NVRAM, any other memory chip orcartridge, and networked versions of the same.

Non-transitory media is distinct from but may be used in conjunctionwith transmission media. Transmission media participates in transferringinformation between non-transitory media. For example, transmissionmedia includes coaxial cables, copper wire and fiber optics, includingthe wires that comprise bus 702. Transmission media can also take theform of acoustic or light waves, such as those generated duringradio-wave and infra-red data communications.

Various forms of media may be involved in carrying one or more sequencesof one or more instructions to processor 704 for execution. For example,the instructions may initially be carried on a magnetic disk or solidstate drive of a remote computer. The remote computer can load theinstructions into its dynamic memory and send the instructions over atelephone line using a modem. A modem local to computer system 700 canreceive the data on the telephone line and use an infra-red transmitterto convert the data to an infra-red signal. An infra-red detector canreceive the data carried in the infra-red signal and appropriatecircuitry can place the data on bus 702. Bus 702 carries the data tomain memory 706, from which processor 704 retrieves and executes theinstructions. The instructions received by main memory 706 may retrievesand executes the instructions. The instructions received by main memory706 may optionally be stored on storage device 710 either before orafter execution by processor 704.

The computer system 700 also includes a communication interface 718coupled to bus 702. Communication interface 718 provides a two-way datacommunication coupling to one or more network links that are connectedto one or more local networks. For example, communication interface 718may be an integrated services digital network (ISDN) card, cable modem,satellite modem, or a modem to provide a data communication connectionto a corresponding type of telephone line. As another example,communication interface 718 may be a local area network (LAN) card toprovide a data communication connection to a compatible LAN (or WANcomponent to communicated with a WAN). Wireless links may also beimplemented. In any such implementation, communication interface 718sends and receives electrical, electromagnetic or optical signals thatcarry digital data streams representing various types of information.

A network link typically provides data communication through one or morenetworks to other data devices. For example, a network link may providea connection through local network to a host computer or to dataequipment operated by an Internet Service Provider (ISP). The ISP inturn provides data communication services through the world wide packetdata communication network now commonly referred to as the “Internet”.Local network and Internet both use electrical, electromagnetic oroptical signals that carry digital data streams. The signals through thevarious networks and the signals on network link and throughcommunication interface 718, which carry the digital data to and fromcomputer system 700, are example forms of transmission media.

The computer system 700 can send messages and receive data, includingprogram code, through the network(s), network link and communicationinterface 718. In the Internet example, a server might transmit arequested code for an application program through the Internet, the ISP,the local network and the communication interface 718.

The received code may be executed by processor 704 as it is received,and/or stored in storage device 710, or other non-volatile storage forlater execution.

Each of the processes, methods, and algorithms described in thepreceding sections may be embodied in, and fully or partially automatedby, code modules executed by one or more computer systems or computerprocessors comprising computer hardware. The processes and algorithmsmay be implemented partially or wholly in application-specificcircuitry.

The various features and processes described above may be usedindependently of one another, or may be combined in various ways. Allpossible combinations and sub-combinations are intended to fall withinthe scope of this disclosure. In addition, certain method or processblocks may be omitted in some implementations. The methods and processesdescribed herein are also not limited to any particular sequence, andthe blocks or states relating thereto can be performed in othersequences that are appropriate. For example, described blocks or statesmay be performed in an order other than that specifically disclosed, ormultiple blocks or states may be combined in a single block or state.The example blocks or states may be performed in serial, in parallel, orin some other manner. Blocks or states may be added to or removed fromthe disclosed example embodiments. The example systems and componentsdescribed herein may be configured differently than described. Forexample, elements may be added to, removed from, or rearranged comparedto the disclosed example embodiments.

Conditional language, such as, among others, “can,” “could,” “might,” or“may,” unless specifically stated otherwise, or otherwise understoodwithin the context as used, is generally intended to convey that certainembodiments include, while other embodiments do not include, certainfeatures, elements and/or steps. Thus, such conditional language is notgenerally intended to imply that features, elements and/or steps are inany way required for one or more embodiments or that one or moreembodiments necessarily include logic for deciding, with or without userinput or prompting, whether these features, elements and/or steps areincluded or are to be performed in any particular embodiment.

Any process descriptions, elements, or blocks in the flow diagramsdescribed herein and/or depicted in the attached figures should beunderstood as potentially representing modules, segments, or portions ofcode which include one or more executable instructions for implementingspecific logical functions or steps in the process. Alternateimplementations are included within the scope of the embodimentsdescribed herein in which elements or functions may be deleted, executedout of order from that shown or discussed, including substantiallyconcurrently or in reverse order, depending on the functionalityinvolved, as would be understood by those skilled in the art.

It should be emphasized that many variations and modifications may bemade to the above-described embodiments, the elements of which are to beunderstood as being among other acceptable examples. All suchmodifications and variations are intended to be included herein withinthe scope of this disclosure. The foregoing description details certainembodiments of the invention. It will be appreciated, however, that nomatter how detailed the foregoing appears in text, the invention can bepracticed in many ways. As is also stated above, it should be noted thatthe use of particular terminology when describing certain features oraspects of the invention should not be taken to imply that theterminology is being re-defined herein to be restricted to including anyspecific characteristics of the features or aspects of the inventionwith which that terminology is associated. The scope of the inventionshould therefore be construed in accordance with the appended claims andany equivalents thereof.

ENGINES, COMPONENTS, AND LOGIC

Certain embodiments are described herein as including logic or a numberof components, engines, or mechanisms. Engines may constitute eithersoftware engines (e.g., code embodied on a machine-readable medium) orhardware engines. A “hardware engine” is a tangible unit capable ofperforming certain operations and may be configured or arranged in acertain physical manner. In various example embodiments, one or morecomputer systems (e.g., a standalone computer system, a client computersystem, or a server computer system) or one or more hardware engines ofa computer system (e.g., a processor or a group of processors) may beconfigured by software (e.g., an application or application portion) asa hardware engine that operates to perform certain operations asdescribed herein.

In some embodiments, a hardware engine may be implemented mechanically,electronically, or any suitable combination thereof. For example, ahardware engine may include dedicated circuitry or logic that ispermanently configured to perform certain operations. For example, ahardware engine may be a special-purpose processor, such as aField-Programmable Gate Array (FPGA) or an Application SpecificIntegrated Circuit (ASIC). A hardware engine may also includeprogrammable logic or circuitry that is temporarily configured bysoftware to perform certain operations. For example, a hardware enginemay include software executed by a general-purpose processor or otherprogrammable processor. Once configured by such software, hardwareengines become specific machines (or specific components of a machine)uniquely tailored to perform the configured functions and are no longergeneral-purpose processors. It will be appreciated that the decision toimplement a hardware engine mechanically, in dedicated and permanentlyconfigured circuitry, or in temporarily configured circuitry (e.g.,configured by software) may be driven by cost and time considerations.

Accordingly, the phrase “hardware engine” should be understood toencompass a tangible entity, be that an entity that is physicallyconstructed, permanently configured (e.g., hardwired), or temporarilyconfigured (e.g., programmed) to operate in a certain manner or toperform certain operations described herein. As used herein,“hardware-implemented engine” refers to a hardware engine. Consideringembodiments in which hardware engines are temporarily configured (e.g.,programmed), each of the hardware engines need not be configured orinstantiated at any one instance in time. For example, where a hardwareengine comprises a general-purpose processor configured by software tobecome a special-purpose processor, the general-purpose processor may beconfigured as respectively different special-purpose processors (e.g.,comprising different hardware engines) at different times. Softwareaccordingly configures a particular processor or processors, forexample, to constitute a particular hardware engine at one instance oftime and to constitute a different hardware engine at a differentinstance of time.

Hardware engines can provide information to, and receive informationfrom, other hardware engines. Accordingly, the described hardwareengines may be regarded as being communicatively coupled. Where multiplehardware engines exist contemporaneously, communications may be achievedthrough signal transmission (e.g., over appropriate circuits and buses)between or among two or more of the hardware engines. In embodiments inwhich multiple hardware engines are configured or instantiated atdifferent times, communications between such hardware engines may beachieved, for example, through the storage and retrieval of informationin memory structures to which the multiple hardware engines have access.For example, one hardware engine may perform an operation and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further hardware engine may then, at a latertime, access the memory device to retrieve and process the storedoutput. Hardware engines may also initiate communications with input oroutput devices, and can operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented enginesthat operate to perform one or more operations or functions describedherein. As used herein, “processor-implemented engine” refers to ahardware engine implemented using one or more processors.

Similarly, the methods described herein may be at least partiallyprocessor-implemented, with a particular processor or processors beingan example of hardware. For example, at least some of the operations ofa method may be performed by one or more processors orprocessor-implemented engines. Moreover, the one or more processors mayalso operate to support performance of the relevant operations in a“cloud computing” environment or as a “software as a service” (SaaS).For example, at least some of the operations may be performed by a groupof computers (as examples of machines including processors), with theseoperations being accessible via a network (e.g., the Internet) and viaone or more appropriate interfaces (e.g., an Application ProgramInterface (API)).

The performance of certain of the operations may be distributed amongthe processors, not only residing within a single machine, but deployedacross a number of machines. In some example embodiments, the processorsor processor-implemented engines may be located in a single geographiclocation (e.g., within a home environment, an office environment, or aserver farm). In other example embodiments, the processors orprocessor-implemented engines may be distributed across a number ofgeographic locations.

LANGUAGE

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Although an overview of the subject matter has been described withreference to specific example embodiments, various modifications andchanges may be made to these embodiments without departing from thebroader scope of embodiments of the present disclosure. Such embodimentsof the subject matter may be referred to herein, individually orcollectively, by the term “invention” merely for convenience and withoutintending to voluntarily limit the scope of this application to anysingle disclosure or concept if more than one is, in fact, disclosed.

The embodiments illustrated herein are described in sufficient detail toenable those skilled in the art to practice the teachings disclosed.Other embodiments may be used and derived therefrom, such thatstructural and logical substitutions and changes may be made withoutdeparting from the scope of this disclosure. The Detailed Description,therefore, is not to be taken in a limiting sense, and the scope ofvarious embodiments is defined only by the appended claims, along withthe full range of equivalents to which such claims are entitled.

It will be appreciated that an “engine,” “system,” “data store,” and/or“database” may comprise software, hardware, firmware, and/or circuitry.In one example, one or more software programs comprising instructionscapable of being executable by a processor may perform one or more ofthe functions of the engines, data stores, databases, or systemsdescribed herein. In another example, circuitry may perform the same orsimilar functions. Alternative embodiments may comprise more, less, orfunctionally equivalent engines, systems, data stores, or databases, andstill be within the scope of present embodiments. For example, thefunctionality of the various systems, engines, data stores, and/ordatabases may be combined or divided differently.

“Open source” software is defined herein to be source code that allowsdistribution as source code as well as compiled form, with awell-publicized and indexed means of obtaining the source, optionallywith a license that allows modifications and derived works.

The data stores described herein may be any suitable structure (e.g., anactive database, a relational database, a self-referential database, atable, a matrix, an array, a flat file, a documented-oriented storagesystem, a non-relational No-SQL system, and the like), and may becloud-based or otherwise.

As used herein, the term “or” may be construed in either an inclusive orexclusive sense. Moreover, plural instances may be provided forresources, operations, or structures described herein as a singleinstance. Additionally, boundaries between various resources,operations, engines, engines, and data stores are somewhat arbitrary,and particular operations are illustrated in a context of specificillustrative configurations. Other allocations of functionality areenvisioned and may fall within a scope of various embodiments of thepresent disclosure. In general, structures and functionality presentedas separate resources in the example configurations may be implementedas a combined structure or resource. Similarly, structures andfunctionality presented as a single resource may be implemented asseparate resources. These and other variations, modifications,additions, and improvements fall within a scope of embodiments of thepresent disclosure as represented by the appended claims. Thespecification and drawings are, accordingly, to be regarded in anillustrative rather than a restrictive sense.

Conditional language, such as, among others, “can,” “could,” “might,” or“may,” unless specifically stated otherwise, or otherwise understoodwithin the context as used, is generally intended to convey that certainembodiments include, while other embodiments do not include, certainfeatures, elements and/or steps. Thus, such conditional language is notgenerally intended to imply that features, elements and/or steps are inany way required for one or more embodiments or that one or moreembodiments necessarily include logic for deciding, with or without userinput or prompting, whether these features, elements and/or steps areincluded or are to be performed in any particular embodiment.

Although the invention has been described in detail for the purpose ofillustration based on what is currently considered to be the mostpractical and preferred implementations, it is to be understood thatsuch detail is solely for that purpose and that the invention is notlimited to the disclosed implementations, but, on the contrary, isintended to cover modifications and equivalent arrangements that arewithin the spirit and scope of the appended claims. For example, it isto be understood that the present invention contemplates that, to theextent possible, one or more features of any embodiment can be combinedwith one or more features of any other embodiment.

1. A system comprising: one or more processors; and a memory storinginstructions that, when executed by the one or more processors, causethe system to perform: providing, responsive to a search query, anobject associated with the search query, wherein the object is stored ina searchable object model managed by a first computing platform andincludes one or more properties, wherein the one or more propertiesinclude at least a textual attribute associated with the text;determining one or more data sets that correspond to a property of theobject; and selectively updating the object to incorporate a subset ofdata from the data sets, based on relevancies of particular portions ofthe data sets to the object.
 2. The system of claim 1, wherein theselective updating of the object is based on respective activitypatterns for the object and the data sets indicating previousconjunctive searches and comparisons between the object and the datasets.
 3. The system of claim 1, wherein the instructions further causethe system to perform: determining an other object that is alsoassociated with the property; and linking the object to the otherobject.
 4. The system of claim 3, wherein the instructions further causethe system to perform: rendering the other object together with theobject.
 5. The system of claim 1, wherein the data sets are stored inone or more tables.
 6. The system of claim 5, wherein the determinationof the data sets is performed within columns, within the tables, thatmatch the property of the object.
 7. The system of claim 1, wherein theobject comprises attributes that comprise: a media; and a relationshipwith another object.
 8. A method being implemented by a computing systemincluding one or more physical processors and storage media storingmachine-readable instructions, the method comprising: providing,responsive to a search query, an object associated with the searchquery, wherein the object is stored in a searchable object model managedby a first computing platform and includes one or more properties,wherein the one or more properties include at least a textual attributeassociated with the text; determining one or more data sets thatcorrespond to a property of the object; and selectively updating theobject to incorporate a subset of data from the data sets, based onrelevancies of particular portions of the data sets to the object. 9.The method of claim 8, wherein the selective updating of the object isbased on respective activity patterns for the object and the data setsindicating previous conjunctive searches and comparisons between theobject and the data sets.
 10. The method of claim 8, further comprising:determining an other object that is also associated with the property;and linking the object to the other object.
 11. The method of claim 10,further comprising: rendering the other object together with the object.12. The method of claim 8, further comprising: storing the data sets inone or more tables.
 13. The method of claim 12, wherein thedetermination of the data sets is performed within columns, within thetables, that match the property of the object.
 14. The method of claim8, wherein the object comprises attributes that comprise: a media; and arelationship with another object.
 15. A non-transitory computer readablemedium comprising instructions that, when executed, cause one or moreprocessors to perform: providing, responsive to a search query, anobject associated with the search query, wherein the object is stored ina searchable object model managed by a first computing platform andincludes one or more properties, wherein the one or more propertiesinclude at least a textual attribute associated with the text;determining one or more data sets that correspond to a property of theobject; and selectively updating the object to incorporate a subset ofdata from the data sets, based on relevancies of particular portions ofthe data sets to the object.
 16. The non-transitory computer readablemedium of claim 15, wherein the selective updating of the object isbased on respective activity patterns for the object and the data setsindicating previous conjunctive searches and comparisons between theobject and the data sets.
 17. The non-transitory computer readablemedium of claim 15, wherein the instructions further cause the one ormore processors to perform: determining an other object that is alsoassociated with the property; and linking the object to the otherobject.
 18. The non-transitory computer readable medium of claim 17,wherein the instructions further cause the one or more processors toperform: rendering the other object together with the object.
 19. Thenon-transitory computer readable medium of claim 15, wherein the datasets are stored in one or more tables, and the determination of the datasets is performed within columns, within the tables, that match theproperty of the object.
 20. The non-transitory computer readable mediumof claim 15, wherein the object comprises attributes that comprise: amedia; and a relationship with another object.